Skip to Main content Skip to Navigation
Theses

Detection of attacks against cyber-physical industrial systems

Abstract : We address security issues in cyber-physical industrial systems. Attacks against these systems shall be handled both in terms of safety and security. Control technologies imposed by industrial standards already cover the safety dimension. From a security standpoint, the literature has shown that using only cyber information to handle the security of cyber-physical systems is not enough, since physical malicious actions are ignored. For this reason, cyber-physical systems have to be protected from threats to their cyber and physical layers. Some authors handle the attacks by using physical attestations of the underlying processes, f.i., physical watermarking to ensure the truthfulness of the process. However, these detectors work properly only if the adversaries do not have enough knowledge to mislead crosslayer data. This thesis focuses on the aforementioned limitations. It starts by testing the effectiveness of a stationary watermark-based fault detector, to detect, as well, malicious actions produced by adversaries. We show that the stationary watermark-based detector is unable to identify cyber-physical adversaries. We show that the approach only detects adversaries that do not attempt to get any knowledge about the system dynamics. We analyze the detection performance of the original design under the presence of adversaries that infer the system dynamics to evade detection. We revisit the original design, using a non-stationary watermark-based design, to handle those adversaries. We also propose a novel approach that combines control and communication strategies. We validate our solutions using numeric simulations and training cyber-physical testbeds
Complete list of metadatas

Cited literature [113 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-01810321
Contributor : Abes Star :  Contact
Submitted on : Thursday, June 7, 2018 - 4:59:15 PM
Last modification on : Monday, August 24, 2020 - 4:16:11 PM
Long-term archiving on: : Saturday, September 8, 2018 - 3:18:38 PM

File

Thesis-JM-Rubio-Hernan_2017TEL...
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-01810321, version 1

Citation

Jose Manuel Rubio Hernan. Detection of attacks against cyber-physical industrial systems. Networking and Internet Architecture [cs.NI]. Institut National des Télécommunications, 2017. English. ⟨NNT : 2017TELE0015⟩. ⟨tel-01810321⟩

Share

Metrics

Record views

772

Files downloads

1325